• Title/Summary/Keyword: Discrete System

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A Variable Precision Rough Set Model for Interval data (구간 데이터를 위한 가변정밀도 러프집합 모형)

  • Kim, Kyeong-Taek
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.34 no.2
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    • pp.30-34
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    • 2011
  • Variable precision rough set models have been successfully applied to problems whose domains are discrete values. However, there are many situations where discrete data is not available. When it comes to the problems with interval values, no variable precision rough set model has been proposed. In this paper, we propose a variable precision rough set model for interval values in which classification errors are allowed in determining if two intervals are same. To build the model, we define equivalence class, upper approximation, lower approximation, and boundary region. Then, we check if each of 11 characteristics on approximation that works in Pawlak's rough set model is valid for the proposed model or not.

Discrete-Time Output Feedback Algorithm for State Consensus of Multi-Agent Systems (다 개체 시스템의 상태 일치를 위한 이산 시간 출력 궤환 협조 제어 알고리즘)

  • Kim, Jae-Yong;Lee, Jin-Young;Kim, Jung-Su
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.3
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    • pp.625-631
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    • 2011
  • This paper presents a discrete-time output feedback consensus algorithm for Multi-Agent Systems (MAS). Under the assumption that an agent is aware of the relative state information about its neighbors, a state feedback consensus algorithm is designed based on Linear Matrix Inequality (LMI) method. In general, however, it is possible to obtain its relative output information rather than the relative state information. To reconcile this problem, an Unknown Input Observer (UIO) is employed in this paper. To this end, first it is shown that the relative state information can be estimated using the UIO and the measured relative output information. Then a certainty-equivalence type output feedback consensus algorithm is proposed by combining the LMI-based state feedback consensus algorithm with the UIO. Finally, simulation results are given to illustrate that the proposed method successfully achieves the state consensus.

A Novel Discrete predictive current control for PM-LSM (PM-LSM에 대한 새로운 예측 전류 제어)

  • Sun Jung-Won;Suh Jin-Ho;Lee Young Jin;Lee Kwon-Soon
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.1220-1222
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    • 2004
  • In this paper, we propose a new discrete-time predictive current controller for a PM-LSM(permanent magnet linear synchronous motor). The main objectives of the current controllers are to ensure that the measured stator currents tract the command values accurately and to shorten the transient interval as much as possible, in order to obtain high-performance of ac drive system. A new control strategy is seen the scheme that gets the fast adaptation of transient current change, the fast transient response tracking and is proposed simplified calculation. Moreover, the simulation results will be verified the improvements of predictive controller and accuracy of the current controller.

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Induction motor rotor speed estimation using discrete adaptive observer (이산 적응 관측자를 이용한 유도전동기의 회전자 속도 추정)

  • Yi, Sang-Chul;Choi, Chang-Ho;Nam, Kwang-Hee
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1060-1062
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    • 1996
  • This paper presents a discrete adaptive observer for MIMO system of an IM model in DQ reference model. The IM model in the stationary frame is discretized and it is transformed into the canonical observer form. The unknown parameter is choosen as rotor speed. The adaptive law for parameter adjustment is obtained as a set of recursive equations which are derived by utilizing an exponentially weighted normalized least-square method. The proposed adaptive observer converges rapidly and is also shown to track time-varying plant parameter quickly. Its effectiveness has been demonstrated by computer simulation.

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Multi-Region Model of Solute Transport in Soil for the Preferential Flow (Preferential 흐름에 의한 토양내의 다영역 용질이동 모델)

  • 안병기
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.42 no.2
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    • pp.71-77
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    • 2000
  • A multi-region model for solute transport through saturated soils has been developed to describe preferential flow. The model consists of numerous discrete pore groups, which are characterized by a discrete dispersion coefficient, flow velocity, and porosity . The hydraulic properties for each pore group are derived from a soil's hydraluic conductivity and soil water characteristic functions . Flow in pore group is described by the classical advection-disersion equation (ADE). An implict finite difference scheme was applied to the governing equation that results in a block-tridiagonal system of equations that is very efficient and allows the soil to be divided into any number of pore groups. The numerical technique is derived from methods used to solve coupled equations in fluid dynamics problems and can also be applied to the transport of interacting solutes. The results of the model are compared to the experimental data from published papers. This paper contributes on the characteristics of the method when applied to the parallel porosity model to describe preferential flow of solutes in soil.

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Level Selection of the Multi-Resolution Analysis(MRA) for Optimum Denoising Performance of the Discrete Wavelet Transform(DWT) (이산 웨이블릿 변환(DWT)의 디노이징 최적 성능을 위한 다해상도 분석의 레벨 선택 연구)

  • Whang, J.Y.;Kim, J.H.
    • Proceedings of the KIPE Conference
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    • 2015.07a
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    • pp.465-466
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    • 2015
  • 배터리 관리시스템(BMS;battery management system)의 중요 고려요소인 SOC(state-of-charge) 및 SOH(state-of-health)의 전기적 등가회로 모델 기반 고성능 추정의 전제 조건은 배터리 단자전압의 안정된 실험데이터 확보이다. 그러나, 예상치 않은 에러로 인해 배터리 단자전압에 노이즈 성분이 포함될 경우 SOC 및 SOH 추정알고리즘의 성능저하가 우려된다. 이를 위해, 본 논문은 이산 웨이블릿 변환(DWT;discrete wavelet transform)의 다해상도 분석(MRA;multi resolution analysis) 레벨에 따른 디노이징 최적 성능을 소개하고자 한다. 하드 임계화(hard-thresholding) 및 소프트 임계화(soft-thresholding) 기법에 따른 디노이징 성능 차이를 보이고, 각 임계화 기법 적용 시 디노이징 최적 성능을 보이는 레벨을 선택한다.

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Analysis of Non-Uniform Inflow Fan Noise (비균일 입류에 의한 팬소음 해석)

  • Chung, Ki-Hoon;Choi, Han-Lim;Yun, Young-Il;Lee, Sang-Hyeon;Lee, Duck-Joo
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2000.11a
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    • pp.106-112
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    • 2000
  • Axial fans are widely used in heavy machines due to their ability to produce high flow rate for cooling of engines. At the same time. the noise generated by these fans causes one of the most serious problems. This work is concerned with the low noise technique of discrete frequency noise. The prediction model. which allowed the calculation of acoustic pressure at the blade passing frequency and it's harmonics. has been developed by Farrasat. This theory is founded upon the acoustic radiation of unsteady forces acting on blade. To calculate the unsteady resultant force over the fan blade. Time-Marching Free-Wake Method are used. The fan noise of fan system having unsymmetric engine-room is predicted. In this paper, the discussion is confined to the performance and discrete noise of axial fan and front part of engine room in heavy equipments.

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Application of the 3D Discrete Wavelet Transformation Scheme to Remotely Sensed Image Classification

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.23 no.5
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    • pp.355-363
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    • 2007
  • The 3D DWT(The Three Dimensional Discrete Wavelet Transform) scheme is potentially regarded as useful one on analyzing both spatial and spectral information. Nevertheless, few researchers have attempted to process or classified remotely sensed images using the 3D DWT. This study aims to apply the 3D DWT to the land cover classification of optical and SAR(Synthetic Aperture Radar) images. Then, their results are evaluated quantitatively and compared with the results of traditional classification technique. As the experimental results, the 3D DWT shows superior classification results to conventional techniques, especially dealing with the high-resolution imagery and SAR imagery. It is thought that the 3D DWT scheme can be extended to multi-temporal or multi-sensor image classification.

Hybrid Systems Modeling and Simulation - Part II: Interoperable Simulation Environment (하이브리드 시스템 모델링 및 시뮬레이션 - 제2부: 시뮬레이터 연동 환경)

  • 임성용;김탁곤
    • Journal of the Korea Society for Simulation
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    • v.10 no.3
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    • pp.15-30
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    • 2001
  • Hybrid simulation may employ different types of simulation based on which models in different system types are developed. The simulation requires simulation time synchronization and data exchange between such simulators, which is called simulators interoperation. This paper develops such interoperable simulation environments for modeling and simulation of hybrid systems whose components consist of continuous and discrete event systems. The environments, one for centerized and the other for distribute, support interoperation between a discrete event simulator of DEVSim++ and a continuous simulator of MATLAB. The centerized environment, HDEVSim++, is developed by extending the sxisting DEVSim++ environment; the distributed environment, HDEVSimHLA, is developed using the HLA/RTl library. Verification of both environments is made and performance comparison between the two using a simple example is presented. .

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A Finite Memory Filter for Discrete-Time Stochastic Linear Delay Systems

  • Song, Il Young;Song, Jin Mo;Jeong, Woong Ji;Gong, Myoung Sool
    • Journal of Sensor Science and Technology
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    • v.28 no.4
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    • pp.216-220
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    • 2019
  • In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.